Understanding tourists’ urban images from big data using convolutional neural networks

Bingxue Wang; Hanliang Wang

doi:10.1117/12.2625572

9 December 2021 Understanding tourists’ urban images from big data using convolutional neural networks

Bingxue Wang, Hanliang Wang

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290V (2021) https://doi.org/10.1117/12.2625572
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

The Internet and social media have become important carriers of destination image dissemination, and the photos on social platforms reflect to a certain extent tourists’ perception preferences in tourist destinations. This paper uses the photos actively uploaded by Xi’an tourists on the Liangbulu website as the research data source, and uses the convolutional neural network model to identify the photo scene, then analyzes the tourism image of Xi’an and its spatial distribution characteristics from the perspective of tourists’ perception. The study shows that the spatial distribution of Xi’an’s building, urban landscape, place/region, transportation, interpretation, night scenery, and water tourism image is generally “concentrated in the city center, sparse and isolated in the periphery”; the people and nature tourism images generally show the characteristics of “sparse and scattered” spatial distribution.

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Bingxue Wang and Hanliang Wang "Understanding tourists’ urban images from big data using convolutional neural networks", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290V (9 December 2021); https://doi.org/10.1117/12.2625572

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KEYWORDS

Convolutional neural networks

Data modeling

Image analysis

Statistical analysis

Analytical research

Cognition

Image processing

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